The Effect of Nano-TiO2 and Welding parameter on Dilution in SAW Process using Fuzzy Logic

Submerged arc welding (SAW), is a high quality arc welding process used in heavy industry. In this process selecting appropriate values for process variables is essential in order to decide upon metal transfer and subsequently control the heat input into the workpiece from which reliable predictions could be made about the metallurgical, mechanical properties and performance of the welded joints. In this paper, thickness of TiO2 nano particles coated on plates along with welding current, arc voltage, welding speed and contact tip-to-plate distance were considered as input variables. Experiments were performed based on rotatable central composite design (RCCD) with five factors, each of them set as its five levels. After that dilution of weld bead was measured as the output variable or the response. Finally weld bead dilution was modeled as a function of input variables and predicted by fuzzy logic. Moreover, it has been concluded that, fuzzy logic is a powerful technique used for predicting the dilution of weldments due to its low error rate as compared with experimental outputs.